CN117111422B - Photomask righting recognition method, system and recognition terminal - Google Patents
Photomask righting recognition method, system and recognition terminal Download PDFInfo
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- 238000004364 calculation method Methods 0.000 claims description 4
- 238000004519 manufacturing process Methods 0.000 description 4
- 238000004458 analytical method Methods 0.000 description 3
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- G—PHYSICS
- G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
- G03F—PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES, e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTOR DEVICES; MATERIALS THEREFOR; ORIGINALS THEREFOR; APPARATUS SPECIALLY ADAPTED THEREFOR
- G03F9/00—Registration or positioning of originals, masks, frames, photographic sheets or textured or patterned surfaces, e.g. automatically
- G03F9/70—Registration or positioning of originals, masks, frames, photographic sheets or textured or patterned surfaces, e.g. automatically for microlithography
- G03F9/7003—Alignment type or strategy, e.g. leveling, global alignment
- G03F9/7046—Strategy, e.g. mark, sensor or wavelength selection
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- G—PHYSICS
- G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
- G03F—PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES, e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTOR DEVICES; MATERIALS THEREFOR; ORIGINALS THEREFOR; APPARATUS SPECIALLY ADAPTED THEREFOR
- G03F9/00—Registration or positioning of originals, masks, frames, photographic sheets or textured or patterned surfaces, e.g. automatically
- G03F9/70—Registration or positioning of originals, masks, frames, photographic sheets or textured or patterned surfaces, e.g. automatically for microlithography
- G03F9/7088—Alignment mark detection, e.g. TTR, TTL, off-axis detection, array detector, video detection
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Abstract
The application discloses a photomask righting identification method, a system and an identification terminal, wherein the photomask righting identification method comprises the following steps: acquiring a photomask image, and determining a plurality of candidate areas in the photomask image; acquiring first black-and-white images corresponding to the candidate areas; calculating the ratio of the occurrence of the first pixel values in each first black-and-white image; determining a first black-and-white image with the first pixel value occurrence ratio within a first preset range as a candidate region containing a positive mark; and identifying whether the photomask is in position according to whether each candidate region contains the position mark. The method and the device can skillfully realize the judgment of the position of the photomask, avoid the error of manual judgment, simultaneously avoid the complexity of directly identifying the content of the mark symbol, and improve the stability of the corresponding photomask positive identification scheme.
Description
Technical Field
The application relates to the technical field of semiconductors, in particular to a photomask righting recognition method, a photomask righting recognition system and a photomask righting recognition terminal.
Background
In the integrated circuit manufacturing process, during the mask receiving stage (i.e., before the mask formally enters the host station), the mask needs to enter the host station in a correct posture and direction, so that the host station can smoothly perform subsequent work. Thus, during the mask receiving stage, it is important to identify whether the mask is in place.
Conventional solutions often require the accurate location of the mask to be located by visual inspection by an engineer. If the problem of the placing position of the photomask is not found by mistake of a visual inspection person, the photomask is caused to downtime of the host computer due to the problem of the position when entering the host computer, and normal production is affected. As can be seen, conventional reticle positive identification schemes suffer from instability.
Disclosure of Invention
In view of this, the present application provides a method, a system and a terminal for identifying the mask alignment, so as to solve the problem of instability in the existing mask alignment identification scheme.
The application provides a photomask righting identification method, which comprises the following steps:
acquiring a photomask image, and determining a plurality of candidate areas in the photomask image;
acquiring first black-and-white images corresponding to the candidate areas;
calculating the ratio of the occurrence of the first pixel value in each first black-and-white image;
determining a first black-and-white image with the first pixel value occurrence ratio within a first preset range as a candidate region containing a positive mark;
and identifying whether the photomask is in position according to whether each candidate region contains the position mark.
Optionally, the mask image is rectangular; the candidate areas are respectively located at the corner positions of the photomask image.
Optionally, the acquiring a mask image, determining a plurality of candidate regions in the mask image includes: acquiring a photomask image, and determining pixel coordinates of each pixel on the photomask image; determining the coordinate range of each candidate region; and determining each candidate region in the photomask image according to each coordinate range.
Optionally, the acquiring the first black-and-white image corresponding to each candidate region includes: acquiring a gray level image corresponding to the photomask image; performing image binarization processing on the gray level image to obtain an initial black-and-white image; and acquiring the first black-and-white image corresponding to each candidate region according to the initial black-and-white image.
Optionally, the performing image binarization processing on the gray-scale image includes: and setting the pixel value of the pixel with the gray value larger than or equal to 127 in the gray image to 255, and setting the pixel value of the pixel with the gray value smaller than 127 to 0.
Optionally, the method for identifying the right position of the photomask further comprises: the first black-and-white image having a ratio of occurrence of the second pixel value within the second preset range is determined as a candidate region not containing the normal mark.
Optionally, the method for determining the first preset range and the second preset range includes: acquiring an image of a photomask comprising a positive mark to obtain a sample image; respectively acquiring second black-and-white images corresponding to each candidate region in the sample image; determining a first sub-image containing the positive mark and a second sub-image not containing the positive mark in the second black-and-white image; determining the first preset range according to the ratio of the first pixel value in the first sub-image; and determining the second preset range according to the occurrence ratio of the second pixel value in the second sub-image.
Optionally, the identifying whether the photomask is aligned according to whether each candidate region contains an alignment mark includes: and if the set candidate region contains the positive mark, judging that the photomask is positive if other candidate regions do not contain positive marks.
The application also provides a photomask alignment recognition system, comprising:
a first acquisition module for acquiring a mask image in which a plurality of candidate regions are determined;
the second acquisition module is used for acquiring first black-and-white images corresponding to the candidate areas;
a first calculation module for calculating a ratio of occurrence of first pixel values in each of the first black-and-white images;
a determining module, configured to determine a first black-and-white image with a ratio of occurrence of the first pixel value within a first preset range as a candidate region containing a positive mark;
and the identification module is used for identifying whether the photomask is in the correct position according to whether each candidate region contains the correct position mark.
The application also provides an identification terminal, which comprises: the device comprises a memory and a processor, wherein the memory stores a photomask positive identification program, and the photomask positive identification program realizes the steps of any photomask positive identification method when being executed by the processor.
According to the photomask right position identification method, system and identification terminal, the first black-and-white image corresponding to each candidate region is obtained through the plurality of candidate regions of the photomask image, so that the difference of the image channel values of the mark symbol region and the non-mark symbol region is amplified, the mark symbol is used or exists or does not exist, the right position mark-containing candidate region is accurately identified by combining the occurrence ratio of the first pixel value in each first black-and-white image, whether the photomask right position is identified according to whether each candidate region contains the right position mark or not is judged, judgment of the position of the photomask can be skillfully achieved, errors of manual judgment are avoided, meanwhile, complexity of directly identifying the content of the mark symbol is avoided, and stability of a corresponding photomask right position identification scheme can be improved. The method and the device can also avoid machine faults caused by the position problem of the photomask when the photomask enters the host machine in the current integrated circuit manufacturing field, optimize corresponding process flows, greatly reduce fault rate on the basis of improving process efficiency and further improve machine efficiency.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly introduced below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart of a mask alignment recognition method according to an embodiment of the present disclosure;
FIG. 2 is a schematic diagram of a mask image and candidate regions according to an embodiment of the present application;
FIG. 3 is a block diagram of a mask alignment recognition system according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application. The various embodiments described below and their technical features can be combined with each other without conflict.
The first aspect of the present application provides a method for identifying the mask alignment, which can be executed by an identification terminal that needs to identify whether the mask is aligned. Referring to fig. 1, the mask alignment recognition method includes the following steps S110 to S150.
S110, acquiring a photomask image, and determining a plurality of candidate areas in the photomask image.
The recognition terminal for executing the mask alignment recognition method can be provided with a shooting module for shooting the mask, the shooting module is adopted for shooting the mask, an initial image of the mask can be obtained, and an image processing tool (such as OpenCV and the like) is used for cutting and the like on the initial image so as to reserve an image of a possible area where a mark symbol appears, and a mask image is obtained. Alternatively, to avoid extraneous factors affecting the end result, the cut-out area (i.e., the remaining image area) may be as small as possible, and can contain the marking of the mask.
Optionally, the mask image is rectangular. Considering that the positive mark symbols (e.g., the "x" word mark symbols) on the mask are typically located on two vertices of one side of the mask, a plurality of candidate regions are respectively defined at respective corner positions of the mask image so as to quickly and accurately locate the possible positive marks. As shown in fig. 2, the pixel size of the mask image in the Y-axis direction is Y, the pixel size of the mask image in the X-axis direction is X, the candidate areas at each corner of the mask image include ds_crop1, ds_crop2, ds_crop3, and ds_crop4, the coordinates of ds_crop1 are image (0:2y1, 0:2x1), the coordinates of ds_crop2 are image (0:2y1, X-2x1:x), the coordinates of ds_crop3 are image (Y-2y1:y, 0:2x1), and the coordinates of ds_crop4 are image (Y-2y1:y, X-2x1:x).
And S120, acquiring the first black-and-white images corresponding to the candidate areas, so that the pixel points on the first black-and-white images only relate to two pixel values, and the two pixel values can comprise a first pixel value and a second pixel value. Wherein the RGB corresponding to the first pixel value may be [0, 0], and the RGB corresponding to the second pixel value may be [255, 255, 255]. The difference between the channel values of the marked symbol region and the non-marked symbol region image can be amplified by converting each candidate region into a corresponding first black-and-white image, and the marked mark can be accurately identified by utilizing the characteristic in the row that the marked symbol (namely the marked mark) exists or does not exist.
S130, calculating the ratio R of the occurrence of the first pixel value in each first black-and-white image b 。
Optionally, the ratio R of the occurrence of the first pixel value in a certain first black-and-white image b The calculation method of (1) may include: dividing the number of pixels of RGB to be the first pixel value in the first black-and-white image by the first pixel valueThe total pixel number in a black-and-white image is used to obtain the ratio R of the first pixel value b . If the ratio of the occurrence of the second pixel value in each first black-and-white image is R w The ratio R of the appearance of the second pixel value in a certain first black-and-white image w The calculation method of (1) may include: dividing the number of pixels of RGB as the second pixel value in the first black-and-white image by the total number of pixels in the first black-and-white image to obtain a ratio R of occurrence of the second pixel value w 。
S140, the ratio R of the first pixel value b The first black-and-white image within the first preset range is determined as a candidate region containing the positive mark.
The first preset range may be preset on the corresponding identification terminal. The first preset range may be determined by performing test analysis on a plurality of other candidate region images containing positive marks as first sample images.
S150, whether the photomask is in place is judged according to whether each candidate region contains a place-alignment mark or not, for example, if one or some candidate regions contain place-alignment marks and other candidate regions do not contain place-alignment marks, the photomask can be judged to be in place.
According to the photomask right position identification method, the first black-and-white images corresponding to the candidate areas are obtained through the plurality of candidate areas of the photomask image, so that the difference of the image channel values of the mark symbol area and the non-mark symbol area is amplified, the characteristics of the mark symbol in the row or the presence or absence of the mark symbol are utilized, the candidate areas containing the right position marks are accurately identified by combining the occurrence ratio of the first pixel values in the first black-and-white images, and therefore whether the photomask is right position or not is identified according to whether the candidate areas contain the right position marks or not is identified, judgment of the positions of the photomasks can be skillfully achieved, errors of manual judgment are avoided, meanwhile, the complexity of directly identifying the content of the mark symbol is avoided, and stability of a corresponding photomask right position identification scheme can be improved.
In one embodiment, the acquiring a mask image, determining a plurality of candidate regions in the mask image, includes: acquiring a photomask image, and determining pixel coordinates of each pixel on the photomask image; determining the coordinate range of each candidate region; and determining each candidate region in the photomask image according to each coordinate range so as to quickly and accurately determine each candidate region.
Alternatively, if the positive mark symbol on the mask is located on two vertices of one edge of the mask, the coordinate range of the candidate region may be the coordinate range of each corner on the mask image, and at this time, each candidate region may be quickly determined according to the coordinate range of each corner on the mask image.
In one embodiment, the acquiring the first black-and-white image corresponding to each candidate region includes steps S121 to S123.
S121, acquiring a gray image corresponding to the photomask image.
S122, performing image binarization processing on the gray level image to obtain an initial black-and-white image.
S123, acquiring the first black-and-white image corresponding to each candidate region according to the initial black-and-white image; for example, in the initial black-and-white image, a first black-and-white image corresponding to each candidate region is determined according to the coordinate range of each candidate region.
In one example, in the step S122, the image binarizing process is performed on the gray-scale image, including: and setting the pixel value of the pixel with the gray value larger than or equal to 127 in the gray image to 255, and setting the pixel value of the pixel with the gray value smaller than 127 to 0. The present example binarizes the gray scale image by a threshold 127 such that the resulting initial black and white image is either black or white, with pixels only involving the two pixel values, a first pixel value and a second pixel value.
In one embodiment, the method for identifying the positive position of the photomask further comprises: the ratio R at which the second pixel value appears w The first black-and-white image within the second preset range is determined as a candidate region without the positive mark. The second preset range may be determined by performing test analysis on a plurality of other candidate region images that do not contain the positive marks as second sample images.
Optionally, if the first preset range is T 1 (+/-delt), a second preset range of T 2 If the candidate regions contain positive marks, it can be determined with reference to table 1, in which 1 represents a meaning positive mark and 0 represents a non-positive mark.
TABLE 1
In one example, the method for determining the first preset range and the second preset range includes: acquiring an image of a photomask comprising a positive mark to obtain a sample image; respectively acquiring second black-and-white images corresponding to each candidate region in the sample image; determining a first sub-image containing the positive mark and a second sub-image not containing the positive mark in the second black-and-white image; determining the first preset range according to the ratio of the first pixel value in the first sub-image; and determining the second preset range according to the occurrence ratio of the second pixel value in the second sub-image. Wherein the positive sign may include the symbol "×" or the like.
Optionally, determining the first preset range according to a ratio of occurrence of the first pixel value in the first sub-image includes: calculating an average value T of the ratios of the first pixel values appearing in the respective first sub-images 1 Determining a first preset range as T 1 (+ -delt, i.e. from T 1 -delt to T 1 +delt, delt represents a range adjustment parameter, which may be determined by means of test analysis or the like.
Optionally, determining the second preset range according to a ratio of occurrence of the second pixel value in the second sub-image includes: calculating an average value T of the ratios of the second pixel values appearing in the respective second sub-images 2 Determining the second preset range as T 2 (+ -delt, i.e. from T 2 -delt to T 2 +delt。
In one embodiment, the identifying whether the mask is in place based on whether each of the candidate regions contains a place marker includes: and if the set candidate region contains the positive mark, judging that the photomask is positive if other candidate regions do not contain positive marks.
The positive marks of the mask may be placed in known locations, and the candidate areas set above are determined based on the known positive mark locations on the mask. The embodiment can stably identify whether the photomask is in the right position.
Optionally, taking the mask shown in fig. 2 as an example to describe the above mask positive identification method, the positive mark of the mask may be set with two candidate areas ds_crop1 and ds_crop2, where the two candidate areas ds_crop1 and ds_crop2 are set candidate areas, as shown in table 2, 1 represents a positive mark, 0 represents that the positive mark is not included, and if the two candidate areas ds_crop1 and ds_crop2 both include positive marks, the positive position of the mask may be determined, the corresponding device position is correct, and the mask may be subjected to subsequent processing; if the two candidate regions ds_crop1 and ds_crop2 do not contain the positive marks, or at least one of the other candidate regions contains the positive marks, the mask can be determined to be misplaced, and the mask needs to be adjusted to the positive position for subsequent processing. In table 2, the results that the positive-bit flag recognition result may exist are combined with the following four { positive bits: 1100. south: 0011. west position: 1010. east: 0101, wherein the south, west and east bits all characterize the mask position as incorrect.
TABLE 2
According to the mask righting identification method, the first black-and-white images corresponding to the candidate areas are obtained through the plurality of candidate areas of the mask image, so that the difference of the image channel values of the mark symbol area and the non-mark symbol area is amplified, the characteristic that the mark symbol exists or does not exist in the row is utilized, the candidate areas containing the righting marks are accurately identified according to the occurrence ratio of the first pixel values in the first black-and-white images, whether the mask is righting or not is identified according to whether the righting marks are contained in the candidate areas, judgment on the positions of the mask can be skillfully achieved, errors of manual judgment are avoided, meanwhile, the complexity of directly identifying the content of the mark symbol is avoided, and stability of a corresponding mask righting identification scheme can be improved. The machine fault caused by the position problem of the photomask when the photomask enters the host machine in the current integrated circuit manufacturing field can be avoided, the corresponding process flow can be optimized, the fault rate is greatly reduced on the basis of improving the process efficiency, and the machine efficiency is further improved.
The second aspect of the present application provides a mask alignment recognition system, where the mask alignment recognition system may be provided at a recognition terminal that needs to recognize whether the mask is aligned. Referring to fig. 3, the mask alignment recognition system includes:
a first acquiring module 110, configured to acquire a mask image, and determine a plurality of candidate areas in the mask image;
a second obtaining module 120, configured to obtain first black-and-white images corresponding to the candidate areas;
a first calculating module 130 for calculating a ratio of occurrence of the first pixel values in each of the first black-and-white images;
a determining module 140, configured to determine a first black-and-white image with a ratio of occurrence of the first pixel value within a first preset range as a candidate region containing a positive mark;
the identifying module 150 is configured to identify whether the mask is in place according to whether each candidate region contains a placement mark.
For specific limitations of the mask alignment recognition system, reference may be made to the above limitation of the mask alignment recognition method, and no further description is given here. The units in the mask alignment recognition system may be implemented in whole or in part by software, hardware, or a combination thereof. The units can be embedded in hardware or independent of an operation module in the computer equipment, and can also be stored in a memory in the computer equipment in a software mode, so that the operation module can call and execute the operations corresponding to the units.
The application also provides an identification terminal, which comprises: the device comprises a memory and a processor, wherein the memory stores a photomask positive identification program, and the photomask positive identification program realizes the steps of the photomask positive identification method according to any embodiment when being executed by the processor.
The present application also provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the reticle alignment recognition method according to any of the embodiments above.
Although the application has been shown and described with respect to one or more implementations, equivalent alterations and modifications will occur to others skilled in the art based upon a reading and understanding of this specification and the annexed drawings. This application is intended to cover all such modifications and variations, and is limited only by the scope of the appended claims. In particular regard to the various functions performed by the above described components, the terms used to describe such components are intended to correspond, unless otherwise indicated, to any component which performs the specified function of the described component (e.g., that is functionally equivalent), even though not structurally equivalent to the disclosed structure which performs the function in the herein illustrated exemplary implementations of the specification.
That is, the foregoing embodiments are merely examples of the present application, and are not intended to limit the scope of the patent application, and all equivalent structures or equivalent processes using the descriptions and the contents of the present application, such as the combination of technical features of the embodiments, or direct or indirect application to other related technical fields, are included in the scope of the patent protection of the present application.
In addition, in the description of the present application, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings are merely for convenience in describing the present application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present application. In addition, the present application may use the same or different reference numerals for structural elements having the same or similar characteristics. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more features. In the description of the present application, the meaning of "a plurality" is two or more, unless explicitly defined otherwise.
In this application, the term "exemplary" is used to mean "serving as an example, instance, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments. The previous description is provided to enable any person skilled in the art to make or use the present application. In the above description, various details are set forth for purposes of explanation. It will be apparent to one of ordinary skill in the art that the present application may be practiced without these specific details. In other instances, well-known structures and processes have not been shown in detail to avoid unnecessarily obscuring the description of the present application. Thus, the present application is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed herein.
Claims (10)
1. A photomask righting recognition method is characterized by comprising the following steps:
acquiring a photomask image, and determining a plurality of candidate areas in the photomask image;
acquiring first black-and-white images corresponding to the candidate areas;
calculating the ratio of the occurrence of the first pixel value in each first black-and-white image;
determining a first black-and-white image with the first pixel value occurrence ratio within a first preset range as a candidate region containing a positive mark;
and identifying whether the photomask is in position according to whether each candidate region contains the position mark.
2. The method of claim 1, wherein the mask image is rectangular; the candidate areas are respectively located at the corner positions of the photomask image.
3. The method of claim 1, wherein the acquiring a mask image, determining a plurality of candidate regions in the mask image, comprises:
acquiring a photomask image, and determining pixel coordinates of each pixel on the photomask image;
determining the coordinate range of each candidate region;
and determining each candidate region in the photomask image according to each coordinate range.
4. The method of claim 1, wherein the obtaining a first black-and-white image corresponding to each candidate region comprises:
acquiring a gray level image corresponding to the photomask image;
performing image binarization processing on the gray level image to obtain an initial black-and-white image;
and acquiring the first black-and-white image corresponding to each candidate region according to the initial black-and-white image.
5. The method of claim 4, wherein performing image binarization on the gray scale image comprises:
and setting the pixel value of the pixel with the gray value larger than or equal to 127 in the gray image to 255, and setting the pixel value of the pixel with the gray value smaller than 127 to 0.
6. The method of claim 1, wherein the method further comprises:
the first black-and-white image having a ratio of occurrence of the second pixel value within the second preset range is determined as a candidate region not containing the normal mark.
7. The method of claim 6, wherein the determining the first and second predetermined ranges comprises:
acquiring an image of a photomask comprising a positive mark to obtain a sample image;
respectively acquiring second black-and-white images corresponding to each candidate region in the sample image;
determining a first sub-image containing the positive mark and a second sub-image not containing the positive mark in the second black-and-white image;
determining the first preset range according to the ratio of the first pixel value in the first sub-image;
and determining the second preset range according to the occurrence ratio of the second pixel value in the second sub-image.
8. The method of claim 1, wherein the identifying whether the mask is in place based on whether each of the candidate regions contains a positive mark comprises:
and if the set candidate region contains the positive mark, judging that the photomask is positive if other candidate regions do not contain positive marks.
9. A reticle alignment recognition system, comprising:
a first acquisition module for acquiring a mask image in which a plurality of candidate regions are determined;
the second acquisition module is used for acquiring first black-and-white images corresponding to the candidate areas;
a first calculation module for calculating a ratio of occurrence of first pixel values in each of the first black-and-white images;
a determining module, configured to determine a first black-and-white image with a ratio of occurrence of the first pixel value within a first preset range as a candidate region containing a positive mark;
and the identification module is used for identifying whether the photomask is in the correct position according to whether each candidate region contains the correct position mark.
10. An identification terminal, characterized in that the identification terminal comprises: a memory, and a processor, wherein the memory stores a mask positive identification program, and the mask positive identification program when executed by the processor implements the steps of the mask positive identification method according to any one of claims 1 to 8.
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| CN103412428A (en) * | 2013-07-24 | 2013-11-27 | 北京京东方光电科技有限公司 | Aligning system |
| CN109690408A (en) * | 2016-09-09 | 2019-04-26 | 优志旺电机株式会社 | Substrate Angle Position determines method |
| CN116047874A (en) * | 2023-03-03 | 2023-05-02 | 苏州源卓光电科技有限公司 | Monitoring method of processing equipment |
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2023
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| JPH02307167A (en) * | 1989-05-23 | 1990-12-20 | Matsushita Electric Ind Co Ltd | Position recognizer |
| KR20050078408A (en) * | 2004-01-29 | 2005-08-05 | 삼성에스디아이 주식회사 | Method of alignment for exposure and pattern masks for the method |
| CN103412428A (en) * | 2013-07-24 | 2013-11-27 | 北京京东方光电科技有限公司 | Aligning system |
| CN109690408A (en) * | 2016-09-09 | 2019-04-26 | 优志旺电机株式会社 | Substrate Angle Position determines method |
| CN116047874A (en) * | 2023-03-03 | 2023-05-02 | 苏州源卓光电科技有限公司 | Monitoring method of processing equipment |
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